Preface

In recent years, the optimization of supply chains in the agri-food and animal industries has been a topic of significant research and study. With the increasing complexity and challenges faced by these industries, finding efficient and sustainable solutions has become crucial. In this context, technology integration explores how emerging technologies such as the Internet of Things (IoT), blockchain and artificial intelligence (AI) can be integrated into the supply chain management of industries. Furthermore, the sustainability focus emphasizes the importance of viable practices in supply chain optimization. It explores how incorporating sustainability metrics into decision-making processes can lead to reducing environmental impact and increasing social responsibility. This could include considering factors such as carbon emissions, water usage and ethical sourcing practices, when designing and managing supply chains. In addition to these concepts, this book addresses the need for resilient supply chains in the face of unforeseen events and disruptions, such as natural disasters or disease outbreaks. It explores strategies for risk management, including diversifying sourcing locations, implementing contingency plans and using technology to quickly adapt to changing circumstances.

This book aims to provide an overview of recent studies conducted in the field of agri-food supply chain optimization and animal industry. It also explores the impact of climate change on the food–energy–water nexus, with a focus on Poland as a case study. Additionally, this book discusses the management and analysis of sustainable initiatives in the agri-food supply chain in India, inventory management activities in the Indian sugar supply chain, the dynamics of the rice supply chain system in Punjab, Pakistan and the culture and use of the elderberry bush for the production of elderberry jam. Furthermore, it will delve into the application of the strength Pareto evolutionary algorithm to solve multi-objective transportation problems, the comparison of classical and machine learning forecasting techniques in rice production in India, the prioritization of circular production of olive oil in Tunisia and the role of open innovation as a solution in the food supply chain.

The agri-food supply chain is a complex network of activities involved in the production, processing and distribution of agricultural products. The optimization of this supply chain is essential to ensure efficiency, reduce costs and enhance sustainability. In this context, the first chapter emphasizes the selection of tomato varieties in agri-food supply chain using Delphi–AHP (Analytic Hierarchy Process) methodology and MOORA–MULTIMOORA approaches for an Algerian case study. The tomato variety selection problem (TVSP) is an important decision in agri-food supply chain management. It involves choosing the best tomato variety from a set of alternatives using a set of evaluation criteria. The Delphi method is a formal consensus approach to identifying a problem, selecting panelists, developing a questionnaire and determining whether consensus is reached. The AHP method is considered as a popular multi-criteria decision-making method and is known for its ease of application and efficiency. The problem of tomato variety selection in the agri-food supply chain has not been addressed in previous studies, so the objective of this research is to integrate Delphi, AHP, MULTIMOORA and MOORA approaches to solve this problem. The application of the proposed methodology to the tomato processing company in Algeria, including these three methodologies, the findings and the analysis of the implications of this study are discussed in this chapter.

The second chapter presents an analysis of the current trends in climate change and its effects specifically in Central Europe, especially in Poland due to its vulnerability to water shortages. Climate change has become a significant global concern, impacting various sectors, including agriculture and food production. The main focus of the analysis is on the food–energy–water nexus, which refers to the interconnectedness and interdependence of these three essential resources. In this chapter, the authors discuss the main challenges and opportunities that Poland faces in relation to the food–energy–water nexus. Moreover, they identify knowledge gaps and suggest directions for future research that could lead to sustainable, cost-effective and feasible solutions. These solutions would be applicable not only to Poland but also to other countries in the region that face similar challenges.

Chapter 3 discusses a study that aims to identify sustainable initiatives in the agricultural food product business. It includes a literature review and inputs from domain specialists to identify these initiatives that focus on optimizing environmental and socio-economic factors. In this chapter, the authors prove that these initiatives have a significant impact on the agricultural food product business. In order to analyze these initiatives, researchers use the fuzzy analytic hierarchy process (FAHP) approach. This approach is a decision-making method that allows consideration of multiple criteria and their relative importance. By applying the FAHP approach, it is possible to provide findings that have managerial and policy implications for key stakeholders.

Chapter 4 describes the objectives and methodology of a study on inventory management activities in the sugar industry. Inventory management plays a crucial role in ensuring the smooth functioning of supply chains, including the Indian sugar supply chain. This chapter aims to identify issues related to inventory management and explores the impact of IT applications in facilitating inventory management. The first part of the chapter identifies relevant issues associated with managing inventory activities. In addition, the second part involves the application of factor analysis to determine the factors that govern inventory management activities in the sugar industry. Furthermore, researchers use the regression method to establish a relationship between these issues and the facilitation provided by IT applications. As a final step, the hypotheses are tested using ANOVA to determine whether the relationships observed in the regression analysis are statistically significant.

Chapter 5 discusses the importance of rice as the second most important cereal crop in Pakistan, with a significant portion consumed domestically and the rest exported to the Gulf countries. Rice is a staple crop in Punjab, Pakistan and its supply chain system is of significant importance to the region’s economy. This chapter aims to understand the dynamics and market margins of the rice value chain in domestic markets, and to identify barriers and opportunities for sustainable development. Data was collected through questionnaires and focus group interviews with key actors in the rice value chain. The analysis revealed problems such as a lack of extension services, infrastructure and marketing information systems, which contribute to vulnerability in the chain. Commission agents and wholesalers were found to have the largest share of the marketing margin. The main highlighted parts of this chapter are the need for advanced production technologies, skilled labor, input subsidies and the development of micro-institutions to support smallholder farmers in a sustainable manner.

Chapter 6 focuses on the four-dimensional, multi-objective transportation problem in the General Company for Food Stuff Trading. Transportation plays a critical role in the agri-food supply chain, ensuring the timely and efficient delivery of goods. This chapter aims to manage the transportation process by considering transportation costs, time and distance for different demand and supply centers, distribution lines and means of transportation. The researchers use the strength Pareto evolutionary algorithm and MATLAB program to solve the transportation model and obtain the lowest transportation cost, time and distance. The objectives of this chapter include using realistic applied cases, integrating AI algorithms, speeding up program execution using the decoding procedure and analyzing the homogeneity of objectives in the four-dimensional model using the Pareto group.

Chapter 7 investigates various forecasting methods, including classical methods and machine learning techniques, to predict agricultural rice production in India. Accurate forecasting of rice production is crucial for effective planning and decision-making in the agricultural sector. The time series data from 1949 to 2021 is used for the analysis. Performance metrics such as MAPE (Mean Percentage Error), RMSE (Root Mean Square Error) and MAE (Mean Absolute Error) are used to compare the forecasting methods. The findings prove that the random forest model outperforms other models and predicts a value of 108892.7 thousand tons for rice production in 2022.

Chapter 8 aims to help decision-makers choose sustainable agricultural practices, transformation methods and waste management for the life cycle of the olive oil chain. Circular production, which minimizes waste and maximizes resource efficiency, has become a key concept in sustainable development. By applying circular economy principles and using life cycle analysis methods, different scenarios can be identified and compared to determine the most sustainable option. The study focuses on evaluating the sustainability of existing olive systems in Tunisia, based on eight alternatives proposed in the scientific literature.

Chapter 9 explores the role of open innovation in...